Takahashi, Paul Y.

Background Socioeconomic status (SES) is an important predictor for outcomes of chronic diseases. However, it is often unavailable in clinical data. We sought to determine whether an individual housing-based SES index termed HOUSES can influence the likelihood of multiple chronic conditions (MCC) and hospitalisation in a community population. Methods Participants were residents of Olmsted County, Minnesota, aged >18 years, who were enrolled in Mayo Clinic Biobank on 31 December 2010, with follow-up until 31 December 2011. Primary outcome was all-cause hospitalisation over 1 calendar-year. Secondary outcome was MCC determined through a Minnesota Medical Tiering score. A logistic regression model was used to assess the association of HOUSES with the Minnesota tiering score. With adjustment for age, sex and MCC, the association of HOUSES with hospitalisation risk was tested using the Cox proportional hazards model. Results Eligible patients totalled 6402 persons (median age, 57 years; 25th–75th quartiles, 45–68 years). The lowest quartile of HOUSES was associated with a higher Minnesota tiering score after adjustment for age and sex (OR (95% CI) 2.4 (2.0 to 3.1)) when compared with the highest HOUSES quartile. Patients in the lowest HOUSES quartile had higher risk of all-cause hospitalisation (age, sex, MCC-adjusted HR (95% CI) 1.53 (1.18 to 1.98)) compared with those in the highest quartile. Conclusions Low SES, as assessed by HOUSES, was associated with increased risk of hospitalisation and greater MCC health burden. HOUSES may be a clinically useful surrogate for SES to assess risk stratification for patient care and clinical research.

Abstract BACKGROUND: Biobanks collect and store biological samples and data from participants for use in research by multiple investigators. The Mayo Clinic Biobank was established by the Mayo Clinic Center for Individualized Medicine with a goal to support a wide array of health-related research studies at Mayo Clinic, including cancer studies. The Biobank is not focused on any particular disease, however, through annotation by questionnaires, the Mayo electronic medical record (EMR), and the Mayo Cancer Registry, it is a useful clinical research resource for cancer related studies. METHODS: Recruitment started in April 2009. Our goal is 50,000 enrollees. Eligible subjects are adult Mayo Clinic patients, U.S residents, and able to consent. Mailed invitations were sent to patients with appointments in certain Mayo Clinic departments. Each participant completed a health history questionnaire including a wide variety of health information as well as whether they or their 1st-degree relatives had ever been diagnosed with specific cancers. For self-reported cancers, subjects were asked to provide the age they were first diagnosed. Subjects also provided a blood sample and granted research access to clinically collected specimens and data from their Mayo Clinic record, at enrollment and into the future. All research projects utilizing samples from this resource are required to return to the Biobank the data generated from their projects. RESULTS: In the first three years, 21736 subjects consented to participate (30% response rate). Participants are 58% female, 95% White, and range in age from 18 to 97 with a median age of 62. At enrollment, 74% were residents in Minnesota, 6% in Iowa, 4% in Wisconsin, and 15% in the other states. Twelve percent reported being a current smoker, while 59% were never smokers. The most common self-reported cancers at baseline were non-melanoma skin cancer (n=2950), prostate cancer (n=1107), breast cancer (n=941), melanoma (n=692), colorectal cancer (n=296), cervical cancer (n=240), sarcoma (n=233), urinary/bladder (n=211), lymphoma (n=187), thyroid cancer (n=186), endometrial cancer (n=170), kidney cancer (n=163), lung cancer (n=145). Excluding non-melanoma skin cancer, 16188 (74%) (6516 male, 9672 female) self-reported being cancer free at baseline. Data will be presented on the frequency of incident cancers diagnosed since enrollment in the Biobank. To date, the Biobank has served as a source of controls for 17 cancer related studies on genetic susceptibility, including studies of the breast, colon, myeloma, brain, lung, pancreas, endometrium, and kidneys. CONCLUSIONS: The Mayo Clinic Biobank has quickly been established as a valuable resource for cancer researchers at Mayo Clinic - primarily as a source of controls for genetic studies. As the Biobank continues to grow in sample size and length of follow-up, it will also serve as a cohort study of cancer incidence embedded within an EMR of a large health organization. Citation Format: Janet E. Olson, Euijung Ryu, Kiley J. Johnson, Karen Maschke, Jody A. Morrisette, Mark Liebow, Paul Y. Takahashi, Ruchi G. Sharma, Kari S. Anderson, Matthew A. Hathcock, Jyotishman Pathak, Noralane M. Lindor, Timothy J. Beebe, Stephen N. Thibodeau, James R. Cerhan. The Mayo Clinic Biobank - A growing resource for cancer related studies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2515. doi:10.1158/1538-7445.AM2013-2515

SummaryTestosterone (T) impacts luteinizing hormone (LH) secretion through negative feedback via the androgen receptor (AR) in the hypothalamo‐pituitary system. An untested postulate is that increasing body mass index (BMI), abdominal visceral fat (AVF) or total abdominal fat (TAF) with ageing decreases LH secretion by heightening T negative feedback via AR. This hypothesis was tested in a prospective, randomized double‐blind cross‐over study of 19 healthy men comparing the effects of flutamide, a selective non‐steroidal AR antagonist and placebo administration on basal and pulsatile LH secretion as a function of age and obesity measures. To this end, serum levels of 2‐hydroxyflutamide (2‐OHF), a major active flutamide metabolite, were measured by mass spectrometry, and AVF/TAF quantified by abdominal computerized tomography. Statistical analysis showed that antiandrogen administration elevated 6‐h mean LH concentrations to 5.4 ± 1.3 IU/L compared with 3.3 ± 1.2 IU/L for placebo (p < 10−3), and total T by 35% (p < 10−4). The LH‐T concentration product doubled (p < 10−8). According to deconvolution analysis, flutamide exposure increased total LH secretion (p < 10−3) and pulsatile LH secretion (p = 0.0077), along with LH pulse frequency (p = 0.019). Despite feedback inhibition, the LH‐T product declined as a linear function of AVF (p = 0.021) and TAF (p = 0.017). This was explained by the fact that higher BMI was associated with lower 2‐OHF concentrations (R = −0.562, p = 0.012). In contrast, age was associated with less pulsatile LH secretion (R = −0.567, p = 0.011) even when LH responses were normalized to antiantrogen levels. In conclusion, increased AVF, TAF and BMI predict decreased LH and flutamide blood levels, whereas older age is marked by impaired stimulation of pulsatile LH secretion even when normalized for antiandrogen levels, suggesting different mechanisms of regulation by adiposity and age.

AbstractWe provide a mini‐review of how biobanks can support clinical genetics in the era of personalized medicine. We discuss types of biobanks, including disease specific and general biobanks not focused on one disease. We present considerations in setting up a biobank, including consenting and governance, biospecimens, risk factor and related data, informatics, and linkage to electronic health records for phenotyping. We also discuss the uses of biobanks and ongoing considerations, including genotype‐driven recruitment, investigations of gene–environment associations, and the re‐use of data generated from studies. Finally, we present a brief discussion of some of the unresolved issues, such as return of research results and sustaining biobanks over time. In summary, carefully designed biobanks can provide critical research and infrastructure support for clinical genetics in the era of personalized medicine.

Telemedicine practitioners are familiar with multiple barriers to delivering care at a distance. Licensing and reimbursement barriers are well known and are being addressed at national and state levels by the American Telemedicine Association. Another telemedicine barrier comes in the form of quality measures for diabetes. Minnesota medical practices are currently being compared on the proportion of their patients with diabetes who have attained goals for blood pressure, low-density lipoprotein cholesterol, and hemoglobin A1C. The quality measure for blood pressure specifically excludes measurements taken by the patient, thus precluding blood pressure telemonitoring as a way to meet the blood pressure goal. To counter this barrier, advocacy in telemedicine is needed so that telemonitoring as a data collection tool is included in quality measures.

Gonadotrophin-releasing hormone (GnRH) pulsatility is required for optimal luteinizing hormone (LH) secretion, but whether LH pulsatility is required for physiological testosterone (T) secretion is not known. To test the postulate that pulses of recombinant human (rh) LH stimulate greater T secretion than continuous infusion of the same dose, a potent selective GnRH antagonist was administered overnight to 19 healthy men ages 18–49 yr. Subjects then received saline or rhLH intravenously continuously or as 6-min pulses intravenously every 1 or 2 h at the same total dose. Blood was sampled every 10 min for 10 h to quantify T responses. For the four interventions, the descending rank order of mean LH and mean T concentrations was 1-h = 2-h rhLH pulses > continuous rhLH > saline ( P < 10−3). Plateau LH and T concentrations correlated positively ( R2 = 0.943, P = 0.029) as did LH concentrations and LH half-lives ( R2 = 0.962, P = 0.019). Percentage pulsatile T secretion assessed by deconvolution analysis (Keenan DM, Takahashi PY, Liu PY, Roebuck PD, Nehra AX, Iranmanesh A, Veldhuis JD. Endocrinology 147: 2817–2828, 2006) was the highest ( P = 0.019), and half-time to attain peak T concentrations was the shortest ( P < 10−6), for 1-h rhLH pulses. Approximate entropy (a pattern-regularity measure) revealed more orderly T secretion for 1- than 2-h rhLH pulses ( P = 0.0076). Accordingly, a pulsatile LH signal, while not obligatory to maintain mean T concentrations, controls the mean plasma LH concentration and determines quantifiable patterns of T secretion. These data introduce the question whether blood T patterns in turn supervise distinctive target-tissue responses.

The long-lived glycoprotein hormone, human chorionic gonadotropin (hCG), downregulates testosterone (T) biosynthesis in vitro and in vivo in animals and humans. The degree to which short-lived pulses of pituitary luteinizing hormone (LH) do so, particularly at physiological concentrations, is not known. We test the hypothesis that continuous LH infusion compared with bolus injections of LH every 1 h or every 2 h overnight downregulates T secretory responses to a subsequent fixed template of three consecutive intravenous pulses of a physiological amount of recombinant human (rh) LH (triple stimulus). Nineteen healthy men ages 18–49 yr each underwent four separate randomly ordered overnight gonadotropin-releasing hormone-receptor antagonist treatments with superimposed intravenous infusions of saline or rhLH (1-h pulses, 2-h pulses, or continuously). Each 12-h infusion protocol was followed by the triple rhLH-pulse stimulus the next morning. During the triple stimulus, basal (nonpulsatile) as well as total (basal plus pulsatile) T secretion was higher after overnight 2- and 1-h rhLH pulses than after continuous rhLH or saline delivery. Approximate entropy, a probabilistic measure of feedforward-induced irregularity of T concentration time series, was higher after 1-h rhLH pulses than after continuous rhLH. Analytical estimation of pulsatile rhLH-T dose-response measures revealed higher T secretory sensitivity and greater rhLH potency (lower EC50) after exposure to 1-h than 2-h rhLH pulses. Collectively, these data indicate that in vivo dynamics of LH-stimulated T secretion under standardized conditions in men depend on the prior time mode of LH delivery in the bloodstream.